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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Ankur3107/GitHub-Bugs-Prediction-Challenge/blob/main/exploration/Transformer_Model_exploration.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
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        "id": "gNQK_BHI0Sj6",
        "outputId": "e3eb3901-08ac-47be-ec72-843bf233eb65",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 595
        }
      },
      "source": [
        "!pip install transformers"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting transformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/19/22/aff234f4a841f8999e68a7a94bdd4b60b4cebcfeca5d67d61cd08c9179de/transformers-3.3.1-py3-none-any.whl (1.1MB)\n",
            "\u001b[K     |████████████████████████████████| 1.1MB 3.4MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.6/dist-packages (from transformers) (4.41.1)\n",
            "Collecting sacremoses\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/7d/34/09d19aff26edcc8eb2a01bed8e98f13a1537005d31e95233fd48216eed10/sacremoses-0.0.43.tar.gz (883kB)\n",
            "\u001b[K     |████████████████████████████████| 890kB 15.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from transformers) (1.18.5)\n",
            "Requirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from transformers) (0.7)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.6/dist-packages (from transformers) (3.0.12)\n",
            "Collecting tokenizers==0.8.1.rc2\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/80/83/8b9fccb9e48eeb575ee19179e2bdde0ee9a1904f97de5f02d19016b8804f/tokenizers-0.8.1rc2-cp36-cp36m-manylinux1_x86_64.whl (3.0MB)\n",
            "\u001b[K     |████████████████████████████████| 3.0MB 26.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.6/dist-packages (from transformers) (20.4)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.6/dist-packages (from transformers) (2019.12.20)\n",
            "Collecting sentencepiece!=0.1.92\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/d4/a4/d0a884c4300004a78cca907a6ff9a5e9fe4f090f5d95ab341c53d28cbc58/sentencepiece-0.1.91-cp36-cp36m-manylinux1_x86_64.whl (1.1MB)\n",
            "\u001b[K     |████████████████████████████████| 1.1MB 37.0MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from transformers) (2.23.0)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (1.15.0)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (7.1.2)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (0.16.0)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.6/dist-packages (from packaging->transformers) (2.4.7)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (2020.6.20)\n",
            "Building wheels for collected packages: sacremoses\n",
            "  Building wheel for sacremoses (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sacremoses: filename=sacremoses-0.0.43-cp36-none-any.whl size=893257 sha256=fa20fc2e28822dea70421d0d13d7f12b191dde4f5e846fc418aff06ce602776d\n",
            "  Stored in directory: /root/.cache/pip/wheels/29/3c/fd/7ce5c3f0666dab31a50123635e6fb5e19ceb42ce38d4e58f45\n",
            "Successfully built sacremoses\n",
            "Installing collected packages: sacremoses, tokenizers, sentencepiece, transformers\n",
            "Successfully installed sacremoses-0.0.43 sentencepiece-0.1.91 tokenizers-0.8.1rc2 transformers-3.3.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7-2w0PIX0Zyk"
      },
      "source": [
        "from transformers import *\n",
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iQK3GP8kcYTF",
        "outputId": "4237fb96-82d1-449a-e6f9-9875a94756ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        }
      },
      "source": [
        "!wget https://machinehack-be.s3.amazonaws.com/predict_github_issues_embold_sponsored_hackathon/Embold_Participant%27s_Dataset.zip\n",
        "!unzip ./Embold_Participant\\'s_Dataset.zip -d Dataset"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-10-11 03:43:55--  https://machinehack-be.s3.amazonaws.com/predict_github_issues_embold_sponsored_hackathon/Embold_Participant%27s_Dataset.zip\n",
            "Resolving machinehack-be.s3.amazonaws.com (machinehack-be.s3.amazonaws.com)... 52.219.64.24\n",
            "Connecting to machinehack-be.s3.amazonaws.com (machinehack-be.s3.amazonaws.com)|52.219.64.24|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 102320961 (98M) [application/octet-stream]\n",
            "Saving to: ‘Embold_Participant's_Dataset.zip’\n",
            "\n",
            "Embold_Participant' 100%[===================>]  97.58M  10.2MB/s    in 11s     \n",
            "\n",
            "2020-10-11 03:44:07 (8.85 MB/s) - ‘Embold_Participant's_Dataset.zip’ saved [102320961/102320961]\n",
            "\n",
            "Archive:  ./Embold_Participant's_Dataset.zip\n",
            "   creating: Dataset/Embold_Participant's_Dataset/\n",
            "  inflating: Dataset/Embold_Participant's_Dataset/sample submission.csv  \n",
            "  inflating: Dataset/__MACOSX/Embold_Participant's_Dataset/._sample submission.csv  \n",
            "  inflating: Dataset/Embold_Participant's_Dataset/embold_train_extra.json  \n",
            "  inflating: Dataset/__MACOSX/Embold_Participant's_Dataset/._embold_train_extra.json  \n",
            "  inflating: Dataset/Embold_Participant's_Dataset/embold_test.json  \n",
            "  inflating: Dataset/__MACOSX/Embold_Participant's_Dataset/._embold_test.json  \n",
            "  inflating: Dataset/Embold_Participant's_Dataset/embold_train.json  \n",
            "  inflating: Dataset/__MACOSX/Embold_Participant's_Dataset/._embold_train.json  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_3J63_xQwd64",
        "outputId": "0be1959c-b10a-480e-d8f9-073f1652b30a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "cd \"Dataset/Embold_Participant's_Dataset/\""
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/Dataset/Embold_Participant's_Dataset\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BETqMajBwg3Z",
        "outputId": "534a304b-7747-46fa-deef-34785712d78d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train_df = pd.read_json(\"embold_train.json\").reset_index(drop=True)\n",
        "train_df.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>title</th>\n",
              "      <th>body</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>y-zoom piano roll</td>\n",
              "      <td>a y-zoom on the piano roll would be useful.</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>buggy behavior in selection</td>\n",
              "      <td>! screenshot from 2016-02-23 21 27 40  https:/...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>auto update feature</td>\n",
              "      <td>hi,\\r \\r great job so far, @saenzramiro ! : \\r...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>filter out noisy endpoints in logs</td>\n",
              "      <td>i think we should stop logging requests to:\\r ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>enable pid on / pid off alarm actions for ardu...</td>\n",
              "      <td>expected behavior\\r alarm actions pid on and p...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               title  ... label\n",
              "0                                  y-zoom piano roll  ...     1\n",
              "1                        buggy behavior in selection  ...     0\n",
              "2                                auto update feature  ...     1\n",
              "3                 filter out noisy endpoints in logs  ...     1\n",
              "4  enable pid on / pid off alarm actions for ardu...  ...     0\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TL-5ZoOWwike",
        "outputId": "c9ba8f29-8143-44a4-bc8c-c2bc5edc2ee3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "test_df = pd.read_json(\"embold_test.json\").reset_index(drop=True)\n",
        "test_df.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>title</th>\n",
              "      <th>body</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>config question  path-specific environment var...</td>\n",
              "      <td>issue description or question\\r \\r hey @artemg...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>crash indien vol</td>\n",
              "      <td>de simulator crasht als hij vol zit</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>unable to mine rocks</td>\n",
              "      <td>sarkasmo starting today, when i hit enter  act...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>not all whitelists are processed</td>\n",
              "      <td>create following rules... order of creation is...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>add ctx menu for idafree 70 and idafree 5</td>\n",
              "      <td>associated with .dll, .dll_, .exe, .exe_, .sc,...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               title                                               body\n",
              "0  config question  path-specific environment var...  issue description or question\\r \\r hey @artemg...\n",
              "1                                   crash indien vol                de simulator crasht als hij vol zit\n",
              "2                               unable to mine rocks  sarkasmo starting today, when i hit enter  act...\n",
              "3                   not all whitelists are processed  create following rules... order of creation is...\n",
              "4          add ctx menu for idafree 70 and idafree 5  associated with .dll, .dll_, .exe, .exe_, .sc,..."
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6bs01lvbwog7",
        "outputId": "b5f73ef6-9144-409c-c856-a6603ca9dfa3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train_ex_df = pd.read_json(\"embold_train_extra.json\")\n",
        "train_ex_df.head()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>title</th>\n",
              "      <th>body</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>use a 8bit typeface</td>\n",
              "      <td>since this is meant to emulate some old arcade...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>implement wireless m-bus binding</td>\n",
              "      <td>_from  chris.pa...@googlemail.com  https://cod...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>add multilang support for timeago.js</td>\n",
              "      <td>currently it is only  en . \\r required to add ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>scaleway - seg-fault on shutdown</td>\n",
              "      <td>tbr  irc  creates a new scaleway instance with...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>sistema de pintura: no se guardar los nuevos p...</td>\n",
              "      <td>este sp ya estaba asignado a un carro y se enc...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               title  ... label\n",
              "0                                use a 8bit typeface  ...     1\n",
              "1                   implement wireless m-bus binding  ...     1\n",
              "2               add multilang support for timeago.js  ...     1\n",
              "3                   scaleway - seg-fault on shutdown  ...     0\n",
              "4  sistema de pintura: no se guardar los nuevos p...  ...     0\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MjEvwGHlwqxy"
      },
      "source": [
        "train_data = train_df.append(train_ex_df)\n",
        "test_df['text'] = test_df['title']+' '+test_df['body']\n",
        "train_data['text'] = train_data['title']+' '+train_data['body']"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p3qps5GNw1Gb"
      },
      "source": [
        "test_df['text_len'] = test_df['text'].apply(lambda x: len(x.split(' ')))"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X-thAxG1xS4c"
      },
      "source": [
        "train_data['text_len'] = train_data['text'].apply(lambda x: len(x.split(' ')))"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kt3whBHRxC3p",
        "outputId": "de78b74e-8c4b-41ea-8cfa-8e4c7751b1fc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "test_df['text_len'].plot()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd6a05aa748>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FdPZ03wiy66u",
        "outputId": "cd02bf43-9a73-4c18-adae-2dfaa770067b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "test_df['text_len'].hist()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd69ea21b38>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "quVZuo4FxHDe",
        "outputId": "f059d4aa-b5fd-408e-fbbd-99ce96d090d5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "train_data['text_len'].hist()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd69d9e23c8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zjeXzJu9xXvR",
        "outputId": "8a523acb-16e1-4d88-e48b-9e0ba7a81c00",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "!pip install nlp_profiler"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting nlp_profiler\n",
            "  Downloading https://files.pythonhosted.org/packages/9c/d7/fb0ddce8e09f0438104d8d2f1a729335152b6ab3d9f50bc8f42581aad9bb/nlp_profiler-0.0.1.dev0-py2.py3-none-any.whl\n",
            "Requirement already satisfied: textblob>=0.15.3 in /usr/local/lib/python3.6/dist-packages (from nlp_profiler) (0.15.3)\n",
            "Collecting nltk>=3.5\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/92/75/ce35194d8e3022203cca0d2f896dbb88689f9b3fce8e9f9cff942913519d/nltk-3.5.zip (1.4MB)\n",
            "\u001b[K     |████████████████████████████████| 1.4MB 6.8MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.6/dist-packages (from nlp_profiler) (2.23.0)\n",
            "Collecting tqdm>=4.46.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/bd/cf/f91813073e4135c1183cadf968256764a6fe4e35c351d596d527c0540461/tqdm-4.50.2-py2.py3-none-any.whl (70kB)\n",
            "\u001b[K     |████████████████████████████████| 71kB 6.2MB/s \n",
            "\u001b[?25hCollecting ipython>=7.12.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/23/6a/210816c943c9aeeb29e4e18a298f14bf0e118fe222a23e13bfcc2d41b0a4/ipython-7.16.1-py3-none-any.whl (785kB)\n",
            "\u001b[K     |████████████████████████████████| 788kB 10.5MB/s \n",
            "\u001b[?25hCollecting language-tool-python>=2.3.1\n",
            "  Downloading https://files.pythonhosted.org/packages/62/95/14aae504d437bdd479078249f17f82d3c388ce6b0c7d3b5d23adf1edf11f/language_tool_python-2.4.5-py3-none-any.whl\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from nlp_profiler) (1.1.2)\n",
            "Collecting swifter>=1.0.3\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ef/15/8a38d51ad3ce448956aad35f288da43a5e7aa174d6bfc3f809810d821fd8/swifter-1.0.6.tar.gz (632kB)\n",
            "\u001b[K     |████████████████████████████████| 634kB 26.4MB/s \n",
            "\u001b[?25hCollecting emoji>=0.5.4\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ff/1c/1f1457fe52d0b30cbeebfd578483cedb3e3619108d2d5a21380dfecf8ffd/emoji-0.6.0.tar.gz (51kB)\n",
            "\u001b[K     |████████████████████████████████| 51kB 5.6MB/s \n",
            "\u001b[?25hRequirement already satisfied: joblib>=0.14.1 in /usr/local/lib/python3.6/dist-packages (from nlp_profiler) (0.16.0)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.6/dist-packages (from nltk>=3.5->nlp_profiler) (7.1.2)\n",
            "Requirement already satisfied: regex in /usr/local/lib/python3.6/dist-packages (from nltk>=3.5->nlp_profiler) (2019.12.20)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests>=2.23.0->nlp_profiler) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests>=2.23.0->nlp_profiler) (2020.6.20)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests>=2.23.0->nlp_profiler) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests>=2.23.0->nlp_profiler) (1.24.3)\n",
            "Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.6/dist-packages (from ipython>=7.12.0->nlp_profiler) (50.3.0)\n",
            "Requirement already satisfied: pygments in /usr/local/lib/python3.6/dist-packages (from ipython>=7.12.0->nlp_profiler) (2.6.1)\n",
            "Collecting prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/2b/c1/53ac685833200eb77ef485c2220dac5bfc255418e660790a9eb5cf3abf25/prompt_toolkit-3.0.7-py3-none-any.whl (355kB)\n",
            "\u001b[K     |████████████████████████████████| 358kB 32.3MB/s \n",
            "\u001b[?25hRequirement already satisfied: backcall in /usr/local/lib/python3.6/dist-packages (from ipython>=7.12.0->nlp_profiler) (0.2.0)\n",
            "Requirement already satisfied: pickleshare in /usr/local/lib/python3.6/dist-packages (from ipython>=7.12.0->nlp_profiler) (0.7.5)\n",
            "Requirement already satisfied: pexpect; sys_platform != \"win32\" in /usr/local/lib/python3.6/dist-packages (from ipython>=7.12.0->nlp_profiler) (4.8.0)\n",
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            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/aa/3e/d18f2c04cf2b528e18515999b0c8e698c136db78f62df34eee89cee205f1/psutil-5.7.2.tar.gz (460kB)\n",
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            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/9d/5e/658f152a38a1286f89b5eefef44f5ea7c3ef75d89ff9e7436587c9c852e1/modin-0.8.1.1-py3-none-manylinux1_x86_64.whl (538kB)\n",
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            "Collecting partd>=0.3.10; extra == \"dataframe\"\n",
            "  Downloading https://files.pythonhosted.org/packages/44/e1/68dbe731c9c067655bff1eca5b7d40c20ca4b23fd5ec9f3d17e201a6f36b/partd-1.1.0-py3-none-any.whl\n",
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            "Collecting fsspec>=0.6.0; extra == \"dataframe\"\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/4c/38/39b83c70ff47192255c15da1b602322cb9918682199d5c1d9cf128bdd531/fsspec-0.8.3-py3-none-any.whl (88kB)\n",
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            "Collecting ray>=1.0.0; extra == \"ray\"\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ea/ed/ff896981d4ac684614236f73c1a20cde5f6cb0e2a590c182f62b22706ab4/ray-1.0.0-cp36-cp36m-manylinux1_x86_64.whl (22.9MB)\n",
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            "Collecting locket\n",
            "  Downloading https://files.pythonhosted.org/packages/d0/22/3c0f97614e0be8386542facb3a7dcfc2584f7b83608c02333bced641281c/locket-0.2.0.tar.gz\n",
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            "Collecting redis<3.5.0,>=3.3.2\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/f0/05/1fc7feedc19c123e7a95cfc9e7892eb6cdd2e5df4e9e8af6384349c1cc3d/redis-3.4.1-py2.py3-none-any.whl (71kB)\n",
            "\u001b[K     |████████████████████████████████| 71kB 8.0MB/s \n",
            "\u001b[?25hCollecting colorama\n",
            "  Downloading https://files.pythonhosted.org/packages/c9/dc/45cdef1b4d119eb96316b3117e6d5708a08029992b2fee2c143c7a0a5cc5/colorama-0.4.3-py2.py3-none-any.whl\n",
            "Collecting aiohttp-cors\n",
            "  Downloading https://files.pythonhosted.org/packages/13/e7/e436a0c0eb5127d8b491a9b83ecd2391c6ff7dcd5548dfaec2080a2340fd/aiohttp_cors-0.7.0-py3-none-any.whl\n",
            "Collecting opencensus\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/8a/9c/d40e3408e72d02612acf247d829e3fa9ff15c59f7ad81418ed79962f8681/opencensus-0.7.10-py2.py3-none-any.whl (126kB)\n",
            "\u001b[K     |████████████████████████████████| 133kB 41.5MB/s \n",
            "\u001b[?25hCollecting aiohttp\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/7c/39/7eb5f98d24904e0f6d3edb505d4aa60e3ef83c0a58d6fe18244a51757247/aiohttp-3.6.2-cp36-cp36m-manylinux1_x86_64.whl (1.2MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2MB 42.8MB/s \n",
            "\u001b[?25hCollecting aioredis\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/b0/64/1b1612d0a104f21f80eb4c6e1b6075f2e6aba8e228f46f229cfd3fdac859/aioredis-1.3.1-py3-none-any.whl (65kB)\n",
            "\u001b[K     |████████████████████████████████| 71kB 8.3MB/s \n",
            "\u001b[?25hCollecting colorful\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/b0/8e/e386e248266952d24d73ed734c2f5513f34d9557032618c8910e605dfaf6/colorful-0.5.4-py2.py3-none-any.whl (201kB)\n",
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            "Collecting gpustat\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/b4/69/d8c849715171aeabd61af7da080fdc60948b5a396d2422f1f4672e43d008/gpustat-0.6.0.tar.gz (78kB)\n",
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            "Collecting py-spy>=0.2.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/8e/a7/ab45c9ee3c4654edda3efbd6b8e2fa4962226718a7e3e3be6e3926bf3617/py_spy-0.3.3-py2.py3-none-manylinux1_x86_64.whl (2.9MB)\n",
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            "Collecting opencensus-context==0.1.1\n",
            "  Downloading https://files.pythonhosted.org/packages/2b/b7/720d4507e97aa3916ac47054cd75490de6b6148c46d8c2c487638f16ad95/opencensus_context-0.1.1-py2.py3-none-any.whl\n",
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            "Collecting yarl<2.0,>=1.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/01/c9/379b807a9c298b9694d0af8ee4260be7d40ab1a11fb9d4ae9e70b1e69d96/yarl-1.6.0-cp36-cp36m-manylinux1_x86_64.whl (257kB)\n",
            "\u001b[K     |████████████████████████████████| 266kB 35.6MB/s \n",
            "\u001b[?25hCollecting multidict<5.0,>=4.5\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/1a/95/f50352b5366e7d579e8b99631680a9e32e1b22adfa1629a8f23b1d22d5e2/multidict-4.7.6-cp36-cp36m-manylinux1_x86_64.whl (148kB)\n",
            "\u001b[K     |████████████████████████████████| 153kB 31.4MB/s \n",
            "\u001b[?25hCollecting idna-ssl>=1.0; python_version < \"3.7\"\n",
            "  Downloading https://files.pythonhosted.org/packages/46/03/07c4894aae38b0de52b52586b24bf189bb83e4ddabfe2e2c8f2419eec6f4/idna-ssl-1.1.0.tar.gz\n",
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            "Collecting async-timeout<4.0,>=3.0\n",
            "  Downloading https://files.pythonhosted.org/packages/e1/1e/5a4441be21b0726c4464f3f23c8b19628372f606755a9d2e46c187e65ec4/async_timeout-3.0.1-py3-none-any.whl\n",
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            "Collecting hiredis\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ed/7d/6acf1c8d4f2fb327ff6feec000b4c56a20628fbe966a4c7cd16c0b80343c/hiredis-1.1.0-cp36-cp36m-manylinux2010_x86_64.whl (61kB)\n",
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            "Collecting blessings>=1.6\n",
            "  Downloading https://files.pythonhosted.org/packages/03/74/489f85a78247609c6b4f13733cbf3ba0d864b11aa565617b645d6fdf2a4a/blessings-1.7-py3-none-any.whl\n",
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            "Collecting contextvars; python_version >= \"3.6\" and python_version < \"3.7\"\n",
            "  Downloading https://files.pythonhosted.org/packages/83/96/55b82d9f13763be9d672622e1b8106c85acb83edd7cc2fa5bc67cd9877e9/contextvars-2.4.tar.gz\n",
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            "Collecting immutables>=0.9\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/99/e0/ea6fd4697120327d26773b5a84853f897a68e33d3f9376b00a8ff96e4f63/immutables-0.14-cp36-cp36m-manylinux1_x86_64.whl (98kB)\n",
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            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from google-auth<2.0dev,>=0.4.0->google-api-core<2.0.0,>=1.0.0->opencensus->ray>=1.0.0; extra == \"ray\"->modin[ray]>=0.7.4->swifter>=1.0.3->nlp_profiler) (0.2.8)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth<2.0dev,>=0.4.0->google-api-core<2.0.0,>=1.0.0->opencensus->ray>=1.0.0; extra == \"ray\"->modin[ray]>=0.7.4->swifter>=1.0.3->nlp_profiler) (4.1.1)\n",
            "Requirement already satisfied: pyasn1>=0.1.3 in /usr/local/lib/python3.6/dist-packages (from rsa<5,>=3.1.4; python_version >= \"3\"->google-auth<2.0dev,>=0.4.0->google-api-core<2.0.0,>=1.0.0->opencensus->ray>=1.0.0; extra == \"ray\"->modin[ray]>=0.7.4->swifter>=1.0.3->nlp_profiler) (0.4.8)\n",
            "Building wheels for collected packages: nltk, swifter, emoji, psutil, locket, gpustat, idna-ssl, contextvars\n",
            "  Building wheel for nltk (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for nltk: filename=nltk-3.5-cp36-none-any.whl size=1434678 sha256=e82b5204a7fa09b36f845a2a35c252c0eda02dac95085170da5c8d094165dbf3\n",
            "  Stored in directory: /root/.cache/pip/wheels/ae/8c/3f/b1fe0ba04555b08b57ab52ab7f86023639a526d8bc8d384306\n",
            "  Building wheel for swifter (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for swifter: filename=swifter-1.0.6-cp36-none-any.whl size=13728 sha256=acfb05a2a6b8fa342e5f55d33546f2059d6424e0dbba9f629c4f598c77c72cf4\n",
            "  Stored in directory: /root/.cache/pip/wheels/36/50/86/a1a417f8f2e24d0e7e958341d24405c596fb3af00a40d9408b\n",
            "  Building wheel for emoji (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for emoji: filename=emoji-0.6.0-cp36-none-any.whl size=49716 sha256=42af917d6f079cc0bca89d9c6a11ef1be4f500d4cf0a64f55fe5bd752ee023c2\n",
            "  Stored in directory: /root/.cache/pip/wheels/46/2c/8b/9dcf5216ca68e14e0320e283692dce8ae321cdc01e73e17796\n",
            "  Building wheel for psutil (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for psutil: filename=psutil-5.7.2-cp36-cp36m-linux_x86_64.whl size=279879 sha256=06b898f48493920239acb9b869c34ed6b1e52b17ed5477adf552b163733d7b51\n",
            "  Stored in directory: /root/.cache/pip/wheels/39/a0/f5/c4fa280463e29aea07797acb5312358fefb067c1f4f98e11b1\n",
            "  Building wheel for locket (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for locket: filename=locket-0.2.0-cp36-none-any.whl size=4040 sha256=d46d2de1b60dd07408f867c9b727a3444d9abf45163da85bd71872cd78494938\n",
            "  Stored in directory: /root/.cache/pip/wheels/26/1e/e8/4fa236ec931b1a0cdd61578e20d4934d7bf188858723b84698\n",
            "  Building wheel for gpustat (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gpustat: filename=gpustat-0.6.0-cp36-none-any.whl size=12622 sha256=c910062514b2d57cf3e777e0c627998e94b21be33dcdb81c13b068ade8dbd8b5\n",
            "  Stored in directory: /root/.cache/pip/wheels/48/b4/d5/fb5b7f1d040f2ff20687e3bad6867d63155dbde5a7c10f4293\n",
            "  Building wheel for idna-ssl (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for idna-ssl: filename=idna_ssl-1.1.0-cp36-none-any.whl size=3161 sha256=113fccf2811b02d37a72ffe5deb54478b6fb4e4c782cdb1102cc460d2989033b\n",
            "  Stored in directory: /root/.cache/pip/wheels/d3/00/b3/32d613e19e08a739751dd6bf998cfed277728f8b2127ad4eb7\n",
            "  Building wheel for contextvars (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for contextvars: filename=contextvars-2.4-cp36-none-any.whl size=7666 sha256=f82256f83a6877410c748528cd87a9ab0dd581c459a87bdebab12a34e607b9f6\n",
            "  Stored in directory: /root/.cache/pip/wheels/a5/7d/68/1ebae2668bda2228686e3c1cf16f2c2384cea6e9334ad5f6de\n",
            "Successfully built nltk swifter emoji psutil locket gpustat idna-ssl contextvars\n",
            "\u001b[31mERROR: jupyter-console 5.2.0 has requirement prompt-toolkit<2.0.0,>=1.0.0, but you'll have prompt-toolkit 3.0.7 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: google-colab 1.0.0 has requirement ipython~=5.5.0, but you'll have ipython 7.16.1 which is incompatible.\u001b[0m\n",
            "Installing collected packages: tqdm, nltk, prompt-toolkit, ipython, language-tool-python, psutil, redis, colorama, multidict, yarl, idna-ssl, async-timeout, aiohttp, aiohttp-cors, immutables, contextvars, opencensus-context, opencensus, hiredis, aioredis, colorful, blessings, gpustat, py-spy, ray, modin, swifter, emoji, nlp-profiler, locket, partd, fsspec\n",
            "  Found existing installation: tqdm 4.41.1\n",
            "    Uninstalling tqdm-4.41.1:\n",
            "      Successfully uninstalled tqdm-4.41.1\n",
            "  Found existing installation: nltk 3.2.5\n",
            "    Uninstalling nltk-3.2.5:\n",
            "      Successfully uninstalled nltk-3.2.5\n",
            "  Found existing installation: prompt-toolkit 1.0.18\n",
            "    Uninstalling prompt-toolkit-1.0.18:\n",
            "      Successfully uninstalled prompt-toolkit-1.0.18\n",
            "  Found existing installation: ipython 5.5.0\n",
            "    Uninstalling ipython-5.5.0:\n",
            "      Successfully uninstalled ipython-5.5.0\n",
            "  Found existing installation: psutil 5.4.8\n",
            "    Uninstalling psutil-5.4.8:\n",
            "      Successfully uninstalled psutil-5.4.8\n",
            "Successfully installed aiohttp-3.6.2 aiohttp-cors-0.7.0 aioredis-1.3.1 async-timeout-3.0.1 blessings-1.7 colorama-0.4.3 colorful-0.5.4 contextvars-2.4 emoji-0.6.0 fsspec-0.8.3 gpustat-0.6.0 hiredis-1.1.0 idna-ssl-1.1.0 immutables-0.14 ipython-7.16.1 language-tool-python-2.4.5 locket-0.2.0 modin-0.8.1.1 multidict-4.7.6 nlp-profiler-0.0.1.dev0 nltk-3.5 opencensus-0.7.10 opencensus-context-0.1.1 partd-1.1.0 prompt-toolkit-3.0.7 psutil-5.7.2 py-spy-0.3.3 ray-1.0.0 redis-3.4.1 swifter-1.0.6 tqdm-4.50.2 yarl-1.6.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "IPython",
                  "prompt_toolkit",
                  "psutil",
                  "tqdm"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zp6sFdoK5nv8",
        "outputId": "0174c19d-3e24-4904-e966-4bf577893fe0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "test_df.head()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>title</th>\n",
              "      <th>body</th>\n",
              "      <th>text</th>\n",
              "      <th>text_len</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>config question  path-specific environment var...</td>\n",
              "      <td>issue description or question\\r \\r hey @artemg...</td>\n",
              "      <td>config question  path-specific environment var...</td>\n",
              "      <td>181</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>crash indien vol</td>\n",
              "      <td>de simulator crasht als hij vol zit</td>\n",
              "      <td>crash indien vol de simulator crasht als hij v...</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>unable to mine rocks</td>\n",
              "      <td>sarkasmo starting today, when i hit enter  act...</td>\n",
              "      <td>unable to mine rocks sarkasmo starting today, ...</td>\n",
              "      <td>473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>not all whitelists are processed</td>\n",
              "      <td>create following rules... order of creation is...</td>\n",
              "      <td>not all whitelists are processed create follow...</td>\n",
              "      <td>186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>add ctx menu for idafree 70 and idafree 5</td>\n",
              "      <td>associated with .dll, .dll_, .exe, .exe_, .sc,...</td>\n",
              "      <td>add ctx menu for idafree 70 and idafree 5 asso...</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               title  ... text_len\n",
              "0  config question  path-specific environment var...  ...      181\n",
              "1                                   crash indien vol  ...       10\n",
              "2                               unable to mine rocks  ...      473\n",
              "3                   not all whitelists are processed  ...      186\n",
              "4          add ctx menu for idafree 70 and idafree 5  ...       19\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
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      ]
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            "a856e7180b3c40e783c261464eb410a7"
          ]
        }
      },
      "source": [
        "from nlp_profiler.core import apply_text_profiling\n",
        "\n",
        "new_text_column_dataset = apply_text_profiling(test_df[0:1000], 'text')"
      ],
      "execution_count": 23,
      "outputs": [
        {
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          "text": [
            "final params: {'high_level': True, 'granular': True, 'grammar_check': False, 'spelling_check': True, 'parallelisation_method': 'default'}\n"
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          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-23-0fea80f55285>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mnlp_profiler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcore\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mapply_text_profiling\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mnew_text_column_dataset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mapply_text_profiling\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m1000\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'text'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/nlp_profiler/core.py\u001b[0m in \u001b[0;36mapply_text_profiling\u001b[0;34m(dataframe, text_column, params)\u001b[0m\n\u001b[1;32m     64\u001b[0m         action_function(\n\u001b[1;32m     65\u001b[0m             \u001b[0maction_description\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_dataframe\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 66\u001b[0;31m             \u001b[0mtext_column\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefault_params\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mPARALLELISATION_METHOD_OPTION\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     67\u001b[0m         )\n\u001b[1;32m     68\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/nlp_profiler/spelling_quality_check.py\u001b[0m in \u001b[0;36mapply_spelling_check\u001b[0;34m(heading, new_dataframe, text_column, parallelisation_method)\u001b[0m\n\u001b[1;32m     28\u001b[0m     generate_features(\n\u001b[1;32m     29\u001b[0m         \u001b[0mheading\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mspelling_checks_steps\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m         \u001b[0mnew_dataframe\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparallelisation_method\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m     )\n\u001b[1;32m     32\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/nlp_profiler/generate_features.py\u001b[0m in \u001b[0;36mgenerate_features\u001b[0;34m(main_header, high_level_features_steps, new_dataframe, parallelisation_method)\u001b[0m\n\u001b[1;32m     45\u001b[0m         new_dataframe[new_column] = parallelisation_method_function(\n\u001b[1;32m     46\u001b[0m             \u001b[0msource_field\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtransformation_function\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 47\u001b[0;31m             \u001b[0msource_column\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     48\u001b[0m         )\n\u001b[1;32m     49\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/nlp_profiler/generate_features.py\u001b[0m in \u001b[0;36musing_joblib_parallel\u001b[0;34m(source_field, apply_function, source_column, new_column)\u001b[0m\n\u001b[1;32m     65\u001b[0m         delayed(run_task)(\n\u001b[1;32m     66\u001b[0m             \u001b[0mapply_function\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meach_value\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 67\u001b[0;31m         ) for _, each_value in enumerate(source_values_to_transform)\n\u001b[0m\u001b[1;32m     68\u001b[0m     )\n\u001b[1;32m     69\u001b[0m     \u001b[0msource_values_to_transform\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m   1040\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1041\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mretrieval_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1042\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mretrieve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1043\u001b[0m             \u001b[0;31m# Make sure that we get a last message telling us we are done\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1044\u001b[0m             \u001b[0melapsed_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_start_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/joblib/parallel.py\u001b[0m in \u001b[0;36mretrieve\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    919\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    920\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'supports_timeout'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 921\u001b[0;31m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_output\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    922\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    923\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_output\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/joblib/_parallel_backends.py\u001b[0m in \u001b[0;36mwrap_future_result\u001b[0;34m(future, timeout)\u001b[0m\n\u001b[1;32m    540\u001b[0m         AsyncResults.get from multiprocessing.\"\"\"\n\u001b[1;32m    541\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 542\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    543\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mCfTimeoutError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    544\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mTimeoutError\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.6/concurrent/futures/_base.py\u001b[0m in \u001b[0;36mresult\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    425\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__get_result\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    426\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 427\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_condition\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    428\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    429\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_state\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mCANCELLED\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCANCELLED_AND_NOTIFIED\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.6/threading.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    293\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m    \u001b[0;31m# restore state no matter what (e.g., KeyboardInterrupt)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 295\u001b[0;31m                 \u001b[0mwaiter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0macquire\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    296\u001b[0m                 \u001b[0mgotit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    297\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KImQYBgf9OPr",
        "outputId": "4fb2408d-f130-4856-d432-06052edf6e8a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        }
      },
      "source": [
        "train_data[train_data.label==2].head(10)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>title</th>\n",
              "      <th>body</th>\n",
              "      <th>label</th>\n",
              "      <th>text</th>\n",
              "      <th>text_len</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>proposal  loadtranslation   to lazy load scope...</td>\n",
              "      <td>php\\r public function loadtranslation  \\r {\\r ...</td>\n",
              "      <td>2</td>\n",
              "      <td>proposal  loadtranslation   to lazy load scope...</td>\n",
              "      <td>263</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>null or    in jsonexporter</td>\n",
              "      <td>\\r  \\ rows\\ : {\\r     \\ left\\ :  \\r       {\\r ...</td>\n",
              "      <td>2</td>\n",
              "      <td>null or    in jsonexporter \\r  \\ rows\\ : {\\r  ...</td>\n",
              "      <td>414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>collectionprovider  support pagination</td>\n",
              "      <td>it would be very helpful if support for pagina...</td>\n",
              "      <td>2</td>\n",
              "      <td>collectionprovider  support pagination it woul...</td>\n",
              "      <td>38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>i2cwrite error on debian 9.2:  cannot read pro...</td>\n",
              "      <td>would love for this to be working, but sadly, ...</td>\n",
              "      <td>2</td>\n",
              "      <td>i2cwrite error on debian 9.2:  cannot read pro...</td>\n",
              "      <td>449</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>is performupdatesanimated always necessary whe...</td>\n",
              "      <td>i've been implementing iglistkit on my current...</td>\n",
              "      <td>2</td>\n",
              "      <td>is performupdatesanimated always necessary whe...</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>printing members in network</td>\n",
              "      <td>\\r \\r import scala.collection.mutable.arraybuf...</td>\n",
              "      <td>2</td>\n",
              "      <td>printing members in network \\r \\r import scala...</td>\n",
              "      <td>143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>exceptionhandler  nest can't resolve dependenc...</td>\n",
              "      <td>i'm submitting a...\\r &lt;!-- \\r please search gi...</td>\n",
              "      <td>2</td>\n",
              "      <td>exceptionhandler  nest can't resolve dependenc...</td>\n",
              "      <td>479</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>front end | what time is now?</td>\n",
              "      <td>need to develop a standard time for excluding ...</td>\n",
              "      <td>2</td>\n",
              "      <td>front end | what time is now? need to develop ...</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>how to connection to another tcp server/listen</td>\n",
              "      <td>1. client\\r 2. workerman  websocket server and...</td>\n",
              "      <td>2</td>\n",
              "      <td>how to connection to another tcp server/listen...</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>add functionality to clear additional post met...</td>\n",
              "      <td>let's say you create a bunch of batch processe...</td>\n",
              "      <td>2</td>\n",
              "      <td>add functionality to clear additional post met...</td>\n",
              "      <td>120</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                 title  ... text_len\n",
              "7    proposal  loadtranslation   to lazy load scope...  ...      263\n",
              "11                          null or    in jsonexporter  ...      414\n",
              "14              collectionprovider  support pagination  ...       38\n",
              "16   i2cwrite error on debian 9.2:  cannot read pro...  ...      449\n",
              "50   is performupdatesanimated always necessary whe...  ...       79\n",
              "71                         printing members in network  ...      143\n",
              "74   exceptionhandler  nest can't resolve dependenc...  ...      479\n",
              "106                      front end | what time is now?  ...       57\n",
              "107     how to connection to another tcp server/listen  ...       23\n",
              "115  add functionality to clear additional post met...  ...      120\n",
              "\n",
              "[10 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v0LTX4pg5rf8",
        "outputId": "4b5243e2-9d57-4347-b657-0dec48c5fc12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        }
      },
      "source": [
        "train_data[train_data.label==2].text.values[14]"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "\"lctl_t with kc_caps doesn't work as intended i'm trying to set the a key to function as a  lctl  when held, but  caps  when tapped. to do this i use  ctl_t kc_caps  , however it doesn't function as i'd expect. it seems to toggle  caps  on and off immediately.\\\\r \\\\r if i use a different key for  caps  i can see that tapping the mapped control key turns it off.\\\\r \\\\r is this a limitation of this  ctl_t , or is there another way i can do this?\""
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0dOXakCE9Jtu"
      },
      "source": [
        "bug, feature, question"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}